Designing Crop Insurance to Manage Moral Hazard Costs

A new crop insurance model based on just random risk (natural states) is presented instead of traditional model based on random risk, guaranteed price, and guaranteed yield. The simulation approach shows how the incentive compatibility constraints resolve the moral hazard problem by the insured under the insurer-agency crop insurance contracting.Risk and Uncertainty,

Combat Identification Modeling Using Robust Optimization Techniques

The purposes of this research were: (1) the modeling of a CID situation and (2) the search for robust and controllable input variable settings. The inputs were defined as controllable and noise variables and the confusion matrices in ROC theory were adapted to act as controllable factors. In this research a simple virtual battlespace representation is employed. The experimental results of the CID system are summarized by a posterior confusion matrix and throughout the confusion matrix analysis we can obtain all various types of data such as accuracy, error cost, error rates, and so forth. To find the optimal parameters three evaluation techniques were applied: (1) Linearly constrained discrete optimization, (2) Taguchi’s S|N ratio method and (3) Robust parameter design with a combined array. The results are compared and contrasted across different objective functions. In conclusion, if we consider the diverse characteristics of CID, the simulator needs to focus on finding the controllable parameter that yields the maximum accuracy value. This is because the minimum cost is typically accomplished at the point of maximum accuracy and the cost approach is very subjective depending on the decision maker and battlefield situation. In addition, the most preferable evaluation method is RPD with a combined array due to its superior performance outside of the design space. In the final analysis, we need a detector/classifier that has good performance to minimize error costs and maximize label accuracy

TARGETING ENVIRONMENTAL PROTECTION IN AGRICULTURE: IPM AND BMPS AS ENVIRONMENTAL PERFORMANCE INDICATORS

Nonparametric technical efficiency estimates of potentially polluting input use in soybean and wheat indicate substantial heterogeneity across farms. This implies large costs would be associated with uniform standards or incentives to regulate these inputs. While technical efficiency is not observable, indicators of environmentally beneficial practices are found useful predictors.technical efficiency, DEA, environment performance, pollution, Environmental Economics and Policy,

Sino-ROK relations at 15 : an overview and assessment

For the past 15 years since their diplomatic normalization China and South Korea (ROK) have improved their bilateral ties to such an extent that each represents for the other one of the largest, if not the largest, trade and investment partners. China is also perceived as playing an essential role in the ongoing Six-Party Talks over North Korean nuclear issues and other likely major issues on the Korean peninsula. Yet, there also exists a growing yet littlediscussed list of potential problems and issues underlying their otherwise prosperous relationship. Prime examples include the North Korean “refugees” in China, the history of Koguryo, and the longerterm “rise of China”. After identifying principal trends and major developments in China’s post-Cold War relationships with South Korea in particular and with the two Koreas in general this paper examines actual and likely future differences between China and South Korea on a panoply of peninsular and regional issues, including the evolving US-South Korean alliance relationship. Overall, in short, the current state of the Sino-South Korean relationship can be likened to standing right in the eye of the typhoon without knowing where the shelter is

Monitoring Frequency of Intra‐Fraction Patient Motion Using the ExacTrac System for LINAC‐based SRS Treatments

Purpose: The aim of this study was to investigate the intra‐fractional patient motion using the ExacTrac system in LINAC‐based stereotactic radiosurgery (SRS). Method: A retrospective analysis of 104 SRS patients with kilovoltage image‐guided setup (Brainlab ExacTrac) data was performed. Each patient was imaged pre‐treatment, and at two time points during treatment (1st and 2nd mid‐treatment), and bony anatomy of the skull was used to establish setup error at each time point. The datasets included the translational and rotational setup error, as well as the time period between image acquisitions. After each image acquisition, the patient was repositioned using the calculated shift to correct the setup error. Only translational errors were corrected due to the absence of a 6D treatment table. Setup time and directional shift values were analyzed to determine correlation between shift magnitudes as well as time between acquisitions. Results: The average magnitude translation was 0.64 ± 0.59 mm, 0.79 ± 0.45 mm, and 0.65 ± 0.35 mm for the pre‐treatment, 1st mid‐treatment, and 2nd mid‐treatment imaging time points. The average time from pre‐treatment image acquisition to 1st mid‐treatment image acquisition was 7.98 ± 0.45 min, from 1st to 2nd mid‐treatment image was 4.87 ± 1.96 min. The greatest translation was 3.64 mm, occurring in the pre‐treatment image. No patient had a 1st or 2nd mid‐treatment image with greater than 2 mm magnitude shifts. Conclusion: There was no correlation between patient motion over time, in direction or magnitude, and duration of treatment. The imaging frequency could be reduced to decrease imaging dose and treatment time without significant changes in patient position

Is hyper-selectivity a root of Asian American children's success?

Asian immigrants' children, even those from lower-backgrounds, tend to acquire higher levels of education than other ethnoracial groups, including White natives. Asian culture is often cited as a conventional explanation. The hyper-selectivity hypothesis challenges conventional wisdom by arguing that Asian American culture is an outcome of the community resources associated with hyper-selectivity. In this study, we assess the validity of the hyper-selectivity theory by examining the association between the magnitude of hyper-selectivity measured by the proportion of the BA + degree holders among the 1st generation Asian immigrants across communities and the likelihood of school enrollment for 1.5 and 2nd + generation Asian American children. Our results cast doubt on the hyper-selectivity theory. Asian American children's school enrollment is associated with the magnitude of educational selectivity among Asian immigrants for neither high school nor college. The benefits of hyper-selectivity do not seem to be cross-class or cross Asian ethnic groups. The higher the hyper-selectivity in a community is, the larger the education gap between upper- and lower-background Asian American children. The implications of these findings are discussed

Stress‐Based and Convolutional Forecasting of Injection‐Induced Seismicity: Application to the Otaniemi Geothermal Reservoir Stimulation

Induced seismicity observed during Enhanced Geothermal Stimulation at Otaniemi, Finland is modeled using both statistical and physical approaches. The physical model produces simulations closest to the observations when assuming rate-and-state friction for shear failure with diffusivity matching the pressure build-up at the well-head at onset of injections. Rate-and-state friction implies a time-dependent earthquake nucleation process which is found to be essential in reproducing the spatial pattern of seismicity. This implies that permeability inferred from the expansion of the seismicity triggering front (Shapiro et al., 1997, https://doi.org/10.1111/j.1365-246x.1997.tb01215.x) can be biased. We suggest a heuristic method to account for this bias that is independent of the earthquake magnitude detection threshold. Our modeling suggests that the Omori law decay during injection shut-ins results mainly from stress relaxation by pore pressure diffusion. During successive stimulations, seismicity should only be induced where the previous maximum of Coulomb stress changes is exceeded. This effect, commonly referred to as the Kaiser effect, is not clearly visible in the data from Otaniemi. The different injection locations at the various stimulation stages may have resulted in sufficiently different effective stress distributions that the effect was muted. We describe a statistical model whereby seismicity rate is estimated from convolution of the injection history with a kernel which approximates earthquake triggering by fluid diffusion. The statistical method has superior computational efficiency to the physical model and fits the observations as well as the physical model. This approach is applicable provided the Kaiser effect is not strong, as was the case in Otaniemi

Selection of the Most Probable Best

We consider an expected-value ranking and selection problem where all k solutions' simulation outputs depend on a common uncertain input model. Given that the uncertainty of the input model is captured by a probability simplex on a finite support, we define the most probable best (MPB) to be the solution whose probability of being optimal is the largest. To devise an efficient sampling algorithm to find the MPB, we first derive a lower bound to the large deviation rate of the probability of falsely selecting the MPB, then formulate an optimal computing budget allocation (OCBA) problem to find the optimal static sampling ratios for all solution-input model pairs that maximize the lower bound. We devise a series of sequential algorithms that apply interpretable and computationally efficient sampling rules and prove their sampling ratios achieve the optimality conditions for the OCBA problem as the simulation budget increases. The algorithms are benchmarked against a state-of-the-art sequential sampling algorithm designed for contextual ranking and selection problems and demonstrated to have superior empirical performances at finding the MPB